Update version to v1.4.245 and commit

Together AI Support with OpenAI Fallback Mechanism Added

README.md

@@ -3,7 +3,7 @@ Fabric is graciously supported by…
 
 [![Github Repo Tagline](https://github.com/user-attachments/assets/96ab3d81-9b13-4df4-ba09-75dee7a5c3d2)](https://warp.dev/fabric)
 
-<img src="./images/fabric-logo-gif.gif" alt="fabriclogo" width="400" height="400"/>
+<img src="./docs/images/fabric-logo-gif.gif" alt="fabriclogo" width="400" height="400"/>
 
 # `fabric`
 
@@ -29,7 +29,7 @@ Fabric is graciously supported by…
 [Helper Apps](#helper-apps) •
 [Meta](#meta)
 
-![Screenshot of fabric](images/fabric-summarize.png)
+![Screenshot of fabric](./docs/images/fabric-summarize.png)
 
 </div>
 
@@ -628,7 +628,7 @@ Now let's look at some things you can do with Fabric.
 <br />
 <br />
 
-If you're not looking to do anything fancy, and you just want a lot of great prompts, you can navigate to the [`/patterns`](https://github.com/danielmiessler/fabric/tree/main/patterns) directory and start exploring!
+If you're not looking to do anything fancy, and you just want a lot of great prompts, you can navigate to the [`/patterns`](https://github.com/danielmiessler/fabric/tree/main/data/patterns) directory and start exploring!
 
 We hope that if you used nothing else from Fabric, the Patterns by themselves will make the project useful.
 
@@ -644,7 +644,7 @@ be used in addition to the basic patterns.
 See the [Thinking Faster by Writing Less](https://arxiv.org/pdf/2502.18600) paper and
 the [Thought Generation section of Learn Prompting](https://learnprompting.org/docs/advanced/thought_generation/introduction) for examples of prompt strategies.
 
-Each strategy is available as a small `json` file in the [`/strategies`](https://github.com/danielmiessler/fabric/tree/main/strategies) directory.
+Each strategy is available as a small `json` file in the [`/strategies`](https://github.com/danielmiessler/fabric/tree/main/data/strategies) directory.
 
 The prompt modification of the strategy is applied to the system prompt and passed on to the
 LLM in the chat session.
@@ -736,7 +736,7 @@ Make sure you have a LaTeX distribution (like TeX Live or MiKTeX) installed on y
 It generates a `json` representation of a directory of code that can be fed into an AI model
 with instructions to create a new feature or edit the code in a specified way.
 
-See [the Create Coding Feature Pattern README](./patterns/create_coding_feature/README.md) for details.
+See [the Create Coding Feature Pattern README](./data/patterns/create_coding_feature/README.md) for details.
 
 Install it first using:
 

cmd/fabric/version.go

@@ -1,3 +1,3 @@
 package main
 
-var version = "v1.4.244"
+var version = "v1.4.245"

data/patterns/create_coding_feature/README.md

@@ -7,7 +7,7 @@ Generate code changes to an existing coding project using AI.
 After installing the `code_helper` binary:
 
 ```bash
-go install github.com/danielmiessler/fabric/plugins/tools/code_helper@latest
+go install github.com/danielmiessler/fabric/cmd/code_helper@latest
 ```
 
 ## Usage

internal/plugins/ai/openai_compatible/direct_models_call.go

@@ -0,0 +1,105 @@
+package openai_compatible
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"net/url"
+	"time"
+)
+
+// Model represents a model returned by the API
+type Model struct {
+	ID string `json:"id"`
+}
+
+// ErrorResponseLimit defines the maximum length of error response bodies for truncation.
+const errorResponseLimit = 1024 // Limit for error response body size
+
+// DirectlyGetModels is used to fetch models directly from the API
+// when the standard OpenAI SDK method fails due to a nonstandard format.
+// This is useful for providers like Together that return a direct array of models.
+func (c *Client) DirectlyGetModels(ctx context.Context) ([]string, error) {
+	if ctx == nil {
+		ctx = context.Background()
+	}
+	baseURL := c.ApiBaseURL.Value
+	if baseURL == "" {
+		return nil, fmt.Errorf("API base URL not configured for provider %s", c.GetName())
+	}
+
+	// Build the /models endpoint URL
+	fullURL, err := url.JoinPath(baseURL, "models")
+	if err != nil {
+		return nil, fmt.Errorf("failed to create models URL: %w", err)
+	}
+
+	req, err := http.NewRequestWithContext(ctx, "GET", fullURL, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	req.Header.Set("Authorization", fmt.Sprintf("Bearer %s", c.ApiKey.Value))
+	req.Header.Set("Accept", "application/json")
+
+	// TODO: Consider reusing a single http.Client instance (e.g., as a field on Client) instead of allocating a new one for each request.
+
+	client := &http.Client{
+		Timeout: 10 * time.Second,
+	}
+	resp, err := client.Do(req)
+	if err != nil {
+		return nil, err
+	}
+	defer resp.Body.Close()
+
+	if resp.StatusCode != http.StatusOK {
+		// Read the response body for debugging
+		bodyBytes, _ := io.ReadAll(resp.Body)
+		bodyString := string(bodyBytes)
+		if len(bodyString) > errorResponseLimit { // Truncate if too large
+			bodyString = bodyString[:errorResponseLimit] + "..."
+		}
+		return nil, fmt.Errorf("unexpected status code: %d from provider %s, response body: %s",
+			resp.StatusCode, c.GetName(), bodyString)
+	}
+
+	// Read the response body once
+	bodyBytes, err := io.ReadAll(resp.Body)
+	if err != nil {
+		return nil, err
+	}
+
+	// Try to parse as an object with data field (OpenAI format)
+	var openAIFormat struct {
+		Data []Model `json:"data"`
+	}
+	// Try to parse as a direct array (Together format)
+	var directArray []Model
+
+	if err := json.Unmarshal(bodyBytes, &openAIFormat); err == nil && len(openAIFormat.Data) > 0 {
+		return extractModelIDs(openAIFormat.Data), nil
+	}
+
+	if err := json.Unmarshal(bodyBytes, &directArray); err == nil && len(directArray) > 0 {
+		return extractModelIDs(directArray), nil
+	}
+
+	var truncatedBody string
+	if len(bodyBytes) > errorResponseLimit {
+		truncatedBody = string(bodyBytes[:errorResponseLimit]) + "..."
+	} else {
+		truncatedBody = string(bodyBytes)
+	}
+	return nil, fmt.Errorf("unable to parse models response; raw response: %s", truncatedBody)
+}
+
+func extractModelIDs(models []Model) []string {
+	modelIDs := make([]string, 0, len(models))
+	for _, model := range models {
+		modelIDs = append(modelIDs, model.ID)
+	}
+	return modelIDs
+}

internal/plugins/ai/openai_compatible/providers_config.go

@@ -1,6 +1,7 @@
 package openai_compatible
 
 import (
+	"context"
 	"os"
 	"strings"
 
@@ -31,6 +32,19 @@ func NewClient(providerConfig ProviderConfig) *Client {
 	return client
 }
 
+// ListModels overrides the default ListModels to handle different response formats
+func (c *Client) ListModels() ([]string, error) {
+	// First try the standard OpenAI SDK approach
+	models, err := c.Client.ListModels()
+	if err == nil && len(models) > 0 { // only return if OpenAI SDK returns models
+		return models, nil
+	}
+
+	// TODO: Handle context properly in Fabric by accepting and propagating a context.Context
+	// instead of creating a new one here.
+	return c.DirectlyGetModels(context.Background())
+}
+
 // ProviderMap is a map of provider name to ProviderConfig for O(1) lookup
 var ProviderMap = map[string]ProviderConfig{
 	"AIML": {
@@ -83,6 +97,11 @@ var ProviderMap = map[string]ProviderConfig{
 		BaseURL:             "https://api.siliconflow.cn/v1",
 		ImplementsResponses: false,
 	},
+	"Together": {
+		Name:                "Together",
+		BaseURL:             "https://api.together.xyz/v1",
+		ImplementsResponses: false,
+	},
 }
 
 // GetProviderByName returns the provider configuration for a given name with O(1) lookup

nix/pkgs/fabric/version.nix

@@ -1 +1 @@
-"1.4.244"
+"1.4.245"